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Internet of things (IoT) and big data analytics (BDA) for digital manufacturing (DM)
Department of Mathematics, Technion - IIT, Haifa, 3200003, Israe.
School of Mechanical and Aerospace Engineering, Queen’s University Belfast, Belfast, UK.
School of Mechanical and Aerospace Engineering, Queen’s University Belfast, Belfast, UK.
Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Canada.
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2021 (English)In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, p. 1-18Article in journal (Refereed) Published
Abstract [en]

This paper aims to investigate the impact of enterprise architecture (EA) on system capabilities in dealing with changes and uncertainties in globalised business environments. Enterprise information systems are viewed as information systems to acquire, process, and utilise data in decision-making supports at all levels and domains of businesses, and Internet of things (IoT), big data analytics (BDA), and digital manufacturing (DM) are introduced as representative enabling technologies for data collection, processing, and utilisation in manufacturing applications. The historical development of manufacturing technologies is examined to understand the evolution of system paradigms. The Shannon entropy is adopted to measure the complexity of systems and illustrate the roles of EAs in managing system complexity and achieving system stability in the long term. It is our argument that existing EAs sacrifice system flexibility, resilience, and adaptability for the reduction of system complexity; note that higher adaptability is critical to make a manufacturing system successfully. New EA is proposed to maximise system capabilities for higher flexibility, resilience, and adaptability. The potentials of the proposed EA to modern manufacturing are explored to identify critical research topics with illustrative examples from an application perspective.

Place, publisher, year, edition, pages
Informa UK Limited , 2021. p. 1-18
Keywords [en]
big data analytics (BDA), cyber-physical systems (CPSs), digital manufacturing (DM), enterprise architecture (EA), Internet of things (IoT), Sustainable manufacturing, Advanced Analytics, Big data, Data Analytics, Data handling, Decision making, Industrial research, Information systems, Information use, Manufacture, Manufacturing data processing, System stability, Decision making support, Digital manufacturing, Enterprise Architecture, Enterprise information system, Historical development, Manufacturing applications, Manufacturing technologies, Internet of things
National Category
Information Systems, Social aspects
Identifiers
URN: urn:nbn:se:kth:diva-310623DOI: 10.1080/00207543.2021.1953181ISI: 000674816200001Scopus ID: 2-s2.0-85110877790OAI: oai:DiVA.org:kth-310623DiVA, id: diva2:1650095
Note

QC 20220406

Available from: 2022-04-06 Created: 2022-04-06 Last updated: 2022-09-23Bibliographically approved

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Wang, Lihui

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Output format
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